objplot: Objective Function Plot for Sparse PCs

In pcaPP: Robust PCA by Projection Pursuit

Objective Function Plot for Sparse PCs

Description

Plots an objective function (TPO or BIC) of one or more sparse PCs for a series of lambdas.

Usage

  objplot (x, k, ...)

Arguments

x	An opt.TPO or opt.BIC object.
k	This function displays the objective function's values of the k-th component for opt.TPO-objects, or the first k components for opt.BIC-objects.
...	Further arguments passed to or from other functions.

Details

This function operates on the return object of function opt.TPO or opt.BIC. The model (lambda) selected by the minimization of the corresponding criterion is highlighted by a dashed vertical line.

The component the argument k refers to, corresponds to the $pc.noord item of argument x. For more info on the order of sparse PCs see the details section of opt.TPO.

Author(s)

Heinrich Fritz, Peter Filzmoser <[e-mail]>

References

C. Croux, P. Filzmoser, H. Fritz (2011). Robust Sparse Principal Component Analysis Based on Projection-Pursuit, ?? To appear.

See Also

sPCAgrid, princomp

Examples

  set.seed (0)
                      ##  generate test data
  x <- data.Zou (n = 250)

  k.max <- 3          ##  max number of considered sparse PCs

                      ##  arguments for the sPCAgrid algorithm
  maxiter <- 25       ##    the maximum number of iterations
  method <- "sd"      ##    using classical estimations

                      ##  Optimizing the TPO criterion
  oTPO <- opt.TPO (x, k.max = k.max, method = method, maxiter = maxiter)

                      ##  Optimizing the BIC criterion
  oBIC <- opt.BIC (x, k.max = k.max, method = method, maxiter = maxiter)

          ##  Objective function vs. lambda
  par (mfrow = c (2, k.max))
  for (i in 1:k.max)        objplot (oTPO, k = i)
  for (i in 1:k.max)        objplot (oBIC, k = i)

pcaPP documentation built on Sept. 11, 2024, 8:58 p.m.